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College English Classroom Teaching Evaluation Based on Particle Swarm Optimization – Extreme Learning Machine Model

机译:基于粒子群优化-极限学习机模型的大学英语课堂教学评价

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The quality evaluation of English classroom teaching carries great significance in promoting English teaching reform and raising the quality of English education at university level in China. In this paper, a quality evaluation index system is introduced for the classroom teaching of English as a foreign language (EFL), and an EFL classroom teaching quality evaluation model is built based on the PSO-ELM algorithm with an ELM model constructed for comparison. A comparison shows that the PSO-ELM algorithm can obtain better accuracy with less hidden layer neurons, hence lowering the demand upon experiment samples and strengthening the fitting ability of the model. Experiment results show that the PSO-ELM algorithm is feasible to evaluate classroom teaching of English as a foreign language. The designed English classroom teaching quality evaluation index system is thus confirmed as effective, and is expected to improve the quality and management of classroom teaching of English as a foreign language.
机译:英语课堂教学质量评估对促进英语教学改革,提高我国大学英语教学质量具有重要意义。本文引入了一种针对英语作为外语的课堂教学质量评价指标体系,并基于PSO-ELM算法构建了ELF课堂教学质量评价模型,并建立了用于比较的ELM模型。对比表明,PSO-ELM算法在隐藏层神经元更少的情况下可以获得更好的精度,从而降低了对实验样本的需求,增强了模型的拟合能力。实验结果表明,PSO-ELM算法可用于评估英语作为外语的课堂教学。因此,设计的英语课堂教学质量评价指标体系被确认是有效的,有望改善英语作为外语的课堂教学的质量和管理。

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